Most information today is stored electronically and is available on the World Wide Web. This information includes blog posts, articles (e.g., news articles, opinion pieces, etc.), research papers, web pages, and many other types of documents. While having this much information available is useful, it may be very difficult to find information relevant to a particular topic.
Search engines exist today to attempt to find documents on the web that relate to a search string input by the user. However, most search engines base their search on just the words and operators (e.g., “and”, “or”, etc.) entered by a user. When a user searches for a particular topic, the search engine will only find documents that use the entered word or words, which will lead to many relevant documents being completely overlooked. Such search engines cannot provide a good overview of the documents that surround a particular topic.
Furthermore, search engines do not easily identify current and past occurrences in a systematic manner. Users can hope that an article pops up indicating what has happened with a particular company, but there is no guarantee (or even likelihood) of such an article. Furthermore, the search engines do not present a user with any notion of the importance of an occurrence for a company or other entity.